matplotlib
diff --git a/‎examples/animation/random_walk.py
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+8-4Lines changed: 8 additions & 4 deletions b/‎examples/animation/random_walk.py
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+8-4Lines changed: 8 additions & 4 deletions
diff --git a/‎examples/animation/strip_chart.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎examples/animation/strip_chart.py
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎examples/axisartist/demo_axis_direction.py
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+1-3Lines changed: 1 addition & 3 deletions b/‎examples/axisartist/demo_axis_direction.py
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+1-3Lines changed: 1 addition & 3 deletions
diff --git a/‎examples/axisartist/demo_curvelinear_grid2.py
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+1-3Lines changed: 1 addition & 3 deletions b/‎examples/axisartist/demo_curvelinear_grid2.py
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+1-3Lines changed: 1 addition & 3 deletions
diff --git a/‎examples/axisartist/simple_axis_pad.py
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+1-3Lines changed: 1 addition & 3 deletions b/‎examples/axisartist/simple_axis_pad.py
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+1-3Lines changed: 1 addition & 3 deletions
diff --git a/‎examples/event_handling/pick_event_demo2.py
Copy file name to clipboardExpand all lines: examples/event_handling/pick_event_demo2.py
+3-3Lines changed: 3 additions & 3 deletions b/‎examples/event_handling/pick_event_demo2.py
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+3-3Lines changed: 3 additions & 3 deletions
@@ -15,10 +15,14 @@
 
 def gen_rand_line(length, dims=2):
     """
-    Create a line using a random walk algorithm
-
-    length is the number of points for the line.
-    dims is the number of dimensions the line has.
+    Create a line using a random walk algorithm.
+
+    Parameters
+    ----------
+    length : int
+        The number of points of the line.
+    dims : int
+        The number of dimensions of the line.
     """
     line_data = np.empty((dims, length))
     line_data[:, 0] = np.random.rand(dims)
 
@@ -40,7 +40,7 @@ def update(self, y):
 
 
 def emitter(p=0.03):
-    'return a random value with probability p, else 0'
+    """Return a random value in [0, 1) with probability p, else 0."""
     while True:
         v = np.random.rand(1)
         if v > p:
 
@@ -19,9 +19,7 @@
 
 
 def setup_axes(fig, rect):
-    """
-    polar projection, but in a rectangular box.
-    """
+    """Polar projection, but in a rectangular box."""
 
     # see demo_curvelinear_grid.py for details
     tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()
 
@@ -22,9 +22,7 @@
 
 
 def curvelinear_test1(fig):
-    """
-    grid for custom transform.
-    """
+    """Grid for custom transform."""
 
     def tr(x, y):
         sgn = np.sign(x)
 
@@ -19,9 +19,7 @@
 
 
 def setup_axes(fig, rect):
-    """
-    polar projection, but in a rectangular box.
-    """
+    """Polar projection, but in a rectangular box."""
 
     # see demo_curvelinear_grid.py for details
     tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()
 
@@ -3,9 +3,9 @@
 Pick Event Demo2
 ================
 
-compute the mean and standard deviation (stddev) of 100 data sets and plot
-mean vs stddev.  When you click on one of the mu, sigma points, plot the raw
-data from the dataset that generated the mean and stddev.
+Compute the mean (mu) and standard deviation (sigma) of 100 data sets and plot
+mu vs. sigma.  When you click on one of the (mu, sigma) points, plot the raw
+data from the dataset that generated this point.
 """
 import numpy as np
 import matplotlib.pyplot as plt